gobject.io_add_watch continuous callback from pyalsaaudio - python-2.7

I'm trying to create a small custom mixer that suits my needs, using python 2.7 and pyalsaaudio 0.7, but I'm stuck with events got from alsamixer when another program changes the volume values. I tried to understand how other mixers work (for example volti) and, as far as I understand, it should work as expected, but even if the method is similar, I still get a continuous loop of event response from io_add_watch. So, I suppose that I don't understand how io_add_watch works yet.
This is a small version of the code:
class MyMixer(gtk.Window):
def __init__(self):
super(MyMixer, self).__init__()
self.m = alsaaudio.Mixer(control='Headphone', id=1, cardindex=0)
""" here go the mixer widgets """
self.show_all()
fd, event = self.m.polldescriptors()[0]
self.watch = gobject.io_add_watch(fd, event, self.update)
def update(self, *args):
print 'changed'
""" here I update mixer widgets """
return True
mixer = MyMixer()
gtk.main()
What am I getting wrong?

When you get an event from the poll descriptors, you must call snd_mixer_handle_events().
pyalsaaudio has no mechanism for that.

Related

Live Stream text to HTML tamplets

I have a function at the back-end in Django that calculate and return frames speed of a video given to opencv.videoCapture()`. The type of the speed is float.
class video_feed(object):
def __init__(self, pathVideo):
self.cap = cv.VideoCapture(pathVideo)
#some code .....
def __del__(self):
self.cap.release()
def get_frames(self):
#some code ...
return speed_list
This method keep calling the method while the video is working:
def gen_speed(video_feed):
print('this is spped generation method')
while True:
speed = video_feed.get_frames()
yield(speed)
#gzip.gzip_page
def speed_frame(request):
try:
pathVideo = "video_detection/statics/rl4_pb8-7.mp4"
cam = model.video_feed(pathVideo)
#return StreamingHttpResponse(model.gen_test(cam),content_type="text/csv")
return HttpResponse({'speed':cam.get_frames()})
except:
print("speed_frame not working !!!!!!!!!!!!!!!!!!!!!!!!")
But this code doesn't work. I need a way to make the speed stream to my HTML page so I can use it in a chartjs.
Streaming video using OpenCV is woking just fine but when I change the type to float it doesn't work.
I finally found a better way. Which is using Django channels to stream data in JSON format.

How to turn a Django Rest Framework API View into an async one?

I am trying to build a REST API that will manage some machine learning classification tasks. I have written an API view, which when hit, will trigger the start of a classification task (such as: training an SVM classifier with the data the user provided previously). However, this is a long running task, so I would ideally not have the user wait once they have made a request to this view. Instead, I would like to start this task in the background and give them a response immediately. They can later view the results of the classification in a separate view (haven't implemented that yet.)
I am using ASGI_APPLICATION = 'mlxplorebackend.asgi.application' in settings.py.
Here's my API view in views.py
import asyncio
from concurrent.futures import ProcessPoolExecutor
from django import setup as SetupDjango
# ... other imports
loop = asyncio.get_event_loop()
def DummyClassification():
result = sum(i * i for i in range(10 ** 7))
print(result)
return result
# ... other API views
class TaskExecuteView(APIView):
"""
Once an API call is made to this view, the classification algorithm will start being processed.
Depends on:
1. Parser for the classification algorithm type and parameters
2. Classification algorithm implementation
"""
def get(self, request, taskId, *args, **kwargs):
try:
task = TaskModel.objects.get(taskId = taskId)
except TaskModel.DoesNotExist:
raise Http404
else:
# this is basically the classification task for now
# need to turn this to an async view
with ProcessPoolExecutor(initializer = SetupDjango) as pool:
loop.run_in_executor(pool, DummyClassification)
return Response({ "message": "The task with id: {} has been started".format(task.taskId) }, status = status.HTTP_200_OK)
The problem I am facing is the following:
When I do not use with ProcessPoolExecutor(initializer = SetupDjango) as pool: i.e. without the initializer, I get django.core.exceptions.AppRegistryNotReady: Apps aren't loaded yet. (full traceback at: https://paste.ubuntu.com/p/ctjmFNYMXW/)
When I do use the initializer, the view no longer remains async, it gets blocked. The response returns after the task is completed, which is about 5 seconds on my machine. I do realize I am not really making use of asyncio.sleep() inside my DummyClassification() function, but I can't figure out the way to do so.
I am guessing this is not the way to do it, therefore any suggestions would be appreciated. I would like to avoid celery if I can, since that seems a tad bit too complicated for me.
Edit:
If I get rid of ProcessPoolExecutor() and simply do loop.run_in_executor(None, DummyClassification), it works as expected, but then only one worker thread is working on the task, which doesn't seem remotely ideal for a classification task.
This was a ride. I at first went through the pain of setting up celery only to find out that the original problem of the classification task using one CPU core remains. Then I switched to django-rq with redis and it is currently working as expected.
from .tasks import Pipeline
class TaskExecuteView(APIView):
"""
Once an API call is made to this view, the classification algorithm will start being processed.
Depends on:
1. Parser for the classification algorithm type
2. Classification algorithm implementation
"""
def get(self, request, taskId, *args, **kwargs):
try:
task = TaskModel.objects.get(taskId = taskId)
except TaskModel.DoesNotExist:
raise Http404
else:
Pipeline.delay(taskId) # this is async now ✔
# mark this as an in-progress task
TaskModel.objects.filter(taskId = taskId).update(inProgress = True)
return Response({ "message": "The task with id: {}, title: {} has been started".format(task.taskId, task.taskTitle) }, status = status.HTTP_200_OK)
tasks.py
from django_rq import job
#job('default', timeout=3600)
def Pipeline(taskId):
# classification task

how to get ticking timer with dynamic label?

What im trying to do is that whenever cursor is on label it must show the time elapsed since when it is created it does well by subtracting (def on_enter(i)) the value but i want it to be ticking while cursor is still on label.
I tried using after function as newbie i do not understand it well to use on dynamic labels.
any help will be appreciated thx
code:
from Tkinter import *
import datetime
date = datetime.datetime
now = date.now()
master=Tk()
list_label=[]
k=[]
time_var=[]
result=[]
names=[]
def delete(i):
k[i]=max(k)+1
time_var[i]='<deleted>'
list_label[i].pack_forget()
def create():#new func
i=k.index(max(k))
for j in range(i+1,len(k)):
if k[j]==0:
list_label[j].pack_forget()
list_label[i].pack(anchor='w')
time_var[i]=time_now()
for j in range(i+1,len(k)):
if k[j]==0:
list_label[j].pack(anchor='w')
k[i]=0
###########################
def on_enter(i):
list_label[i].configure(text=time_now()-time_var[i])
def on_leave(i):
list_label[i].configure(text=names[i])
def time_now():
now = date.now()
return date(now.year,now.month,now.day,now.hour,now.minute,now.second)
############################
for i in range(11):
lb=Label(text=str(i),anchor=W)
list_label.append(lb)
lb.pack(anchor='w')
lb.bind("<Button-3>",lambda event,i=i:delete(i))
k.append(0)
names.append(str(i))
lb.bind("<Enter>",lambda event,i=i: on_enter(i))
lb.bind("<Leave>",lambda event,i=i: on_leave(i))
time_var.append(time_now())
master.bind("<Control-Key-z>",lambda event: create())
mainloop()
You would use after like this:
###########################
def on_enter(i):
list_label[i].configure(text=time_now()-time_var[i])
list_label[i].timer = list_label[i].after(1000, on_enter, i)
def on_leave(i):
list_label[i].configure(text=names[i])
list_label[i].after_cancel(list_label[i].timer)
However, your approach here is all wrong. You currently have some functions and a list of data. What you should do is make a single object that contains the functions and data together and make a list of those. That way you can write your code for a single Label and just duplicate that. It makes your code a lot simpler partly because you no longer need to keep track of "i". Like this:
import Tkinter as tk
from datetime import datetime
def time_now():
now = datetime.now()
return datetime(now.year,now.month,now.day,now.hour,now.minute,now.second)
class Kiran(tk.Label):
"""A new type of Label that shows the time since creation when the mouse hovers"""
hidden = []
def __init__(self, master=None, **kwargs):
tk.Label.__init__(self, master, **kwargs)
self.name = self['text']
self.time_var = time_now()
self.bind("<Enter>", self.on_enter)
self.bind("<Leave>", self.on_leave)
self.bind("<Button-3>", self.hide)
def on_enter(self, event=None):
self.configure(text=time_now()-self.time_var)
self.timer = self.after(1000, self.on_enter)
def on_leave(self, event=None):
self.after_cancel(self.timer) # cancel the timer
self.configure(text=self.name)
def hide(self, event=None):
self.pack_forget()
self.hidden.append(self) # add this instance to the list of hidden instances
def show(self):
self.time_var = time_now() # reset time
self.pack(anchor='w')
def undo(event=None):
'''if there's any hidden Labels, show one'''
if Kiran.hidden:
Kiran.hidden.pop().show()
def main():
root = tk.Tk()
root.geometry('200x200')
for i in range(11):
lb=Kiran(text=i)
lb.pack(anchor='w')
root.bind("<Control-Key-z>",undo)
root.mainloop()
if __name__ == '__main__':
main()
More notes:
Don't use lambda unless you are forced to; it's known to cause bugs.
Don't use wildcard imports (from module import *), they cause bugs and are against PEP8.
Put everything in functions.
Use long, descriptive names. Single letter names just waste time. Think of names as tiny comments.
Add a lot more comments to your code so that other people don't have to guess what the code is supposed to do.
Try a more beginner oriented forum for questions like this, like learnpython.reddit.com

How to synchronize wxpython Gauge widget with threads in python?

My python project has multiple threads running. I want to add a gauge widget from the wxpython library to show the progress. I want the gauge to fill until my first thread completes. How do I achieve this? I am using Python 2.7 on Windows.
Use wx.CallAfter
def add_to_the_gauge(value):
your_gauge.Value += value
...
#in some thread
def some_thread_running():
wx.CallAfter(add_to_the_gauge, 2)
You need to post events from your worker thread to the main thread asking it to update the gauge, see this overview.
You can use some simple things
remember to import the module:
import os
and then put this on the frame
def __init__(self, *a, **k):
filename = 'game.exe'
self.timer = wx.Timer()
self.Bind(wx.EVT_TIMER, self.OnUpdateGauge, self.timer)
self.timer.Start()
self.proc = os.popen(filename) # start the process
def OnUpdateGauge(self, event):
if self.proc.poll() == None: # return None if still running and 0 if stopped
self.timer.Stop()
return
else:
'''do something with the gauge'''
hope those help

How to have django give a HTTP response before continuing on to complete a task associated to the request?

In my django piston API, I want to yield/return a http response to the the client before calling another function that will take quite some time. How do I make the yield give a HTTP response containing the desired JSON and not a string relating to the creation of a generator object?
My piston handler method looks like so:
def create(self, request):
data = request.data
*other operations......................*
incident.save()
response = rc.CREATED
response.content = {"id":str(incident.id)}
yield response
manage_incident(incident)
Instead of the response I want, like:
{"id":"13"}
The client gets a string like this:
"<generator object create at 0x102c50050>"
EDIT:
I realise that using yield was the wrong way to go about this, in essence what I am trying to achieve is that the client receives a response right away before the server moves onto the time costly function of manage_incident()
This doesn't have anything to do with generators or yielding, but I've used the following code and decorator to have things run in the background while returning the client an HTTP response immediately.
Usage:
#postpone
def long_process():
do things...
def some_view(request):
long_process()
return HttpResponse(...)
And here's the code to make it work:
import atexit
import Queue
import threading
from django.core.mail import mail_admins
def _worker():
while True:
func, args, kwargs = _queue.get()
try:
func(*args, **kwargs)
except:
import traceback
details = traceback.format_exc()
mail_admins('Background process exception', details)
finally:
_queue.task_done() # so we can join at exit
def postpone(func):
def decorator(*args, **kwargs):
_queue.put((func, args, kwargs))
return decorator
_queue = Queue.Queue()
_thread = threading.Thread(target=_worker)
_thread.daemon = True
_thread.start()
def _cleanup():
_queue.join() # so we don't exit too soon
atexit.register(_cleanup)
Perhaps you could do something like this (be careful though):
import threading
def create(self, request):
data = request.data
# do stuff...
t = threading.Thread(target=manage_incident,
args=(incident,))
t.setDaemon(True)
t.start()
return response
Have anyone tried this? Is it safe? My guess is it's not, mostly because of concurrency issues but also due to the fact that if you get a lot of requests, you might also get a lot of processes (since they might be running for a while), but it might be worth a shot.
Otherwise, you could just add the incident that needs to be managed to your database and handle it later via a cron job or something like that.
I don't think Django is built either for concurrency or very time consuming operations.
Edit
Someone have tried it, seems to work.
Edit 2
These kind of things are often better handled by background jobs. The Django Background Tasks library is nice, but there are others of course.
You've turned your view into a generator thinking that Django will pick up on that fact and handle it appropriately. Well, it won't.
def create(self, request):
return HttpResponse(real_create(request))
EDIT:
Since you seem to be having trouble... visualizing it...
def stuff():
print 1
yield 'foo'
print 2
for i in stuff():
print i
output:
1
foo
2